Triple
T32301258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M1 Junction 15 |
E825243
|
entity |
| Predicate | approximateCounty |
P197457
|
FINISHED |
| Object | West Northamptonshire |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: West Northamptonshire | Statement: [M1 Junction 15, approximateCounty, West Northamptonshire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateCounty Context triple: [M1 Junction 15, approximateCounty, West Northamptonshire]
-
A.
hasNearbyCounty
Indicates that one county is geographically close to or directly adjacent to another county.
-
B.
nearestCountySeat
Indicates that one location is the closest county seat geographically to another location.
-
C.
includesCounty
Indicates that a larger geographic or administrative region contains or encompasses a specific county within its boundaries.
-
D.
inCounty
Indicates that one entity is geographically or administratively located within the boundaries of a specified county.
-
E.
countyOfPlace
Indicates that a place is located within or administratively belongs to a specific county.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f349115304819084ee91d345b6c8aa |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fe920a437081908d5174e8cf7a53a6 |
completed | May 9, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69fe919a9a6c8190acb4483f386e6db7 |
completed | May 9, 2026, 1:44 a.m. |
| PDg | Predicate description generation | batch_69fe9208ed708190980fb5061b22ae49 |
completed | May 9, 2026, 1:46 a.m. |
Created at: May 1, 2026, 12:45 a.m.